Navigating 20 AI Use Cases in Healthcare: From Hype to Evidence!

It’s incredibly hard to see through the current AI hype in healthcare. Myriads of potential uses cases, a lot of companies with commercial interest and changing regulations dominate the field.

To see what is really going on and what we can realistically expect from AI to deliver in practice, we have mapped the rapidly expanding universe of AI use cases in healthcare from early-stage “on the horizon” innovations to “safe bets” that are already backed by strong evidence.

We analyzed them on two scales, little evidence to evidence-based (meaning there are studies and peer-reviewed papers proving their efficiency and safety); and low risk to high risk (meaning patients’ lives might be at stake in case of an error).

This yielded four groups:

1) Speculative and risky (little evidence, high risk)
2) On the horizon (little evidence, low risk)
3) Handle with care (evidence-based, high risk)
4) Safe bet (evidence-based, low risk)

Use cases and their categories

Speculative & Risky

• Autonomous AI prescribing
• Mental health chatbots
• Treatment plans and drug interactions
• Simulate trial designs
• Digital twins for personalized simulations

On The Horizon

• Predictive analytics for patient outcomes
• Patient education
• Disease screening and diagnostics
• Track medication adherence
• Resource allocation

Handle With Care

• AI-driven biomarker and drug discovery
• AI-powered clinical documentation
• AI-assisted robotic surgery
• Radiology analysis
• Automated insurance claims processing

Safe Bet

• Monitor wearables and vital signs
• Triaging patients in ER
• ECG interpretation
• Surgical planning
• Patient scheduling

We hope this infographic helps clarify the path ahead: which solutions demand more research and caution (e.g. autonomous AI prescribing, mental health chatbots), and which are ready for prime time (e.g. AI-powered clinical documentation, radiology analysis, ECG interpretation).